code: def _load_resize_and_pad_image(self, index):
      image_path = self._img_file_paths[index]
  
      img = self._read_image(image_path)
      if self._img_stats[index] is None:
          self._prepare_annotations_proposals_and_stats(index, img)
  
      (
          target_w,
          target_h,
          img_width,
          img_height,
          top,
          bottom,
          left,
          right,
          scale,
      ) = self._img_stats[index]
  
      resized = cv2.resize(
          img,
          (target_w, target_h),
          0,
          0,
          interpolation=cv2.INTER_NEAREST,
      )
      resized_with_pad = cv2.copyMakeBorder(
          resized,
          top,
          bottom,
          left,
          right,
          cv2.BORDER_CONSTANT,
          value=self._pad_value,
      )
      if self._flip_image:
          resized_with_pad = cv2.flip(resized_with_pad, 1)
  
      # transpose(2,0,1) converts the image to the HWC format which CNTK expects
      model_arg_rep = np.ascontiguousarray(
          np.array(resized_with_pad, dtype=np.float32).transpose(
              2, 0, 1
          )
      )
  
      # dims = pad_width, pad_height, scaled_image_width, scaled_image_height, orig_img_width, orig_img_height
      dims = (
          self._pad_width,
          self._pad_height,
          target_w,
          target_h,
          img_width,
          img_height,
      )
      if DEBUG:
          return model_arg_rep, dims, resized_with_pad
      return model_arg_rep, dims
  
file_path: CNTK/Examples/Image/Detection/utils/od_reader.py
imports: import zipfile
  import cv2
  import numpy
  import os
  from utils.proposal_helpers import ProposalProvider, compute_targets, compute_image_stats
label_desc: Use image node_id 10 for calling the ObjectDetectionReader obj's underlying member method code with example usage: obj._load_resize_and_pad_image(index) and returns: model_arg_rep,  dims, model_arg_rep,  dims,  resized_with_pad